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. 2022 Dec 10:17:100538.
doi: 10.1016/j.fochx.2022.100538. eCollection 2023 Mar 30.

Essential terminology and considerations for validation of non-targeted methods

Kapil Nichani  1   2 , Steffen Uhlig  3 , Manfred Stoyke  4 , Sabine Kemmlein  4 , Franz Ulberth  5 , Ilka Haase  6 , Maik Döring  6 , Stephan G Walch  7 , Petra Gowik  4
Affiliations

Essential terminology and considerations for validation of non-targeted methods

Kapil Nichani et al. Food Chem X. .

Abstract

Through their suggestive name, non-targeted methods (NTMs) do not aim at a predefined "needle in the haystack." Instead, they exploit all the constituents of the haystack. This new type of analytical method is increasingly finding applications in food and feed testing. However, the concepts, terms, and considerations related to this burgeoning field of analytical testing need to be propagated for the benefit of those associated with academic research, commercial development, or official control. This paper addresses frequently asked questions regarding terminology in connection with NTMs. The widespread development and adoption of these methods also necessitate the need to develop innovative approaches for NTM validation, i.e., evaluating the performance characteristics of a method to determine if it is fit-for-purpose. This work aims to provide a roadmap for approaching NTM validation. In doing so, the paper deliberates on the different considerations that influence the approach to validation and provides suggestions therefor.

Keywords: Food authenticity; Food fraud; Mass spectrometry; Method validation; NGS; NMR; Non-targeted methods; Spectroscopy.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Components of a non-targeted method.
Fig. 2
Fig. 2
Different ways to formulate an NTM, focusing on examples around olive oil testing. The text in the white box adjoining each connecting arrow provides context and examples.
Fig. 3
Fig. 3
Options for validation approaches depending on whether the class definitions can be delimited numerically and whether the method validation utilizes quantitative decision scores or not.
Fig. 4
Fig. 4
Simulations for illustrating the difference between approaches B and D. Consider the decision limit of 2 (red vertical dotted line) for all three simulations. For each simulation, the green circles represent the decision scores for 30 samples. The region beyond the decision limit of 2 and under the probability density curve (shaded red) is the probability of obtaining a false positive result. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
Stages in the development and validation of NTMs.
See this image and copyright information in PMC

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